| About this Abstract |
| Meeting |
NUMISHEET 2022: The 12th International Conference on Numerical Simulation of 3D Sheet Metal Forming Processes
|
| Symposium
|
NUMISHEET 2022
|
| Presentation Title |
Data-based Prediction Model for an Efficient Matching Process in the Body Shop |
| Author(s) |
Arndt Birkert, Johannes Weber, Moritz Nowack, Christian Schwarz, Benjamin Hartmann, Philipp Zimmermann |
| On-Site Speaker (Planned) |
Moritz Nowack |
| Abstract Scope |
Achieving the optimal dimensional accuracy for automotive body parts today is a time and cost intensive process often based on a try and error approach. There're two ways to improve the accuracy in the production process: Early change of tools in Press Shop is one way to significantly influence the accuracy of parts, although resulting in high costs. The other – much more time and cost effective – way is changing the geometry in the Body Shop, although providing a lesser adjustment range. To define a measure in a single joining stage needs expert knowledge, because the dimension change of a single fixture component can have a complex impact on the final assembly. In this publication, a statistical method is presented to characterize the interactions and identify the main factors in dimensional accuracy of assembled body parts. The surrogate model is based on smart data, gathered from experiments and FEM-simulations. |
| Proceedings Inclusion? |
Definite: At-meeting proceedings |